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Get Started with arframe

Source: vignettes/arframe.Rmd
arframe.Rmd

arframe is a regulatory frame for TFLs — submission-ready tables, listings, and figures in RTF, PDF, and HTML from a single specification. You describe the output once; arframe renders it. Change the file extension, the output adapts. No dplyr, no gt, no RMarkdown — just data in, document out.

Your first table 

spec <- tbl_demog |>
  fr_table() |>
  fr_titles("Table 14.1.1", "Demographics and Baseline Characteristics") |>
  fr_hlines("header")
spec
Table 14.1.1
Demographics and Baseline Characteristics
characteristic placebo zom_50mg zom_100mg total group
Subjects, n 45 45 45 135 n
Age (years) age_cont
Mean (SD) 75.0 (6.75) 73.1 (8.43) 75.3 (7.09) 74.4 (7.46) age_cont
Median 74.0 74.0 73.0 74.0 age_cont
Min, Max 65.0, 88.0 55.0, 88.0 55.0, 88.0 55.0, 88.0 age_cont
Age Group, n (%) age_cat
<65 0 7 (15.6) 1 (2.2) 8 (5.9) age_cat
65-80 36 (80.0) 29 (64.4) 31 (68.9) 96 (71.1) age_cat
>80 9 (20.0) 9 (20.0) 13 (28.9) 31 (23.0) age_cat
Sex, n (%) sex
Female 27 (60.0) 28 (62.2) 20 (44.4) 75 (55.6) sex
Male 18 (40.0) 17 (37.8) 25 (55.6) 60 (44.4) sex
Race, n (%) race
White 38 (84.4) 32 (71.1) 35 (77.8) 105 (77.8) race
Black or African American 1 (2.2) 5 (11.1) 5 (11.1) 11 (8.1) race
Asian 6 (13.3) 6 (13.3) 5 (11.1) 17 (12.6) race
American Indian or Alaska Native 0 2 (4.4) 0 2 (1.5) race
BMI (kg/m2) bmi
Mean (SD) 27.1 (4.76) 26.5 (4.60) 24.9 (5.81) 26.1 (5.13) bmi
Median 27.8 25.9 24.6 25.8 bmi
Min, Max 18.7, 42.3 17.3, 36.5 14.2, 44.5 14.2, 44.5 bmi
MMSE Score at Baseline mmse
Mean (SD) 19.9 (3.51) 19.8 (3.36) 19.5 (3.55) 19.7 (3.45) mmse
Median 20.0 20.0 19.0 20.0 mmse
Min, Max 13.0, 26.0 13.0, 26.0 13.0, 26.0 13.0, 26.0 mmse
Study Completion, n (%) completion
Completed 44 (97.8) 41 (91.1) 37 (82.2) 122 (90.4) completion
Discontinued 1 (2.2) 4 (8.9) 8 (17.8) 13 (9.6) completion
/tmp/RtmpKCCmfM/callr-scr-6801c2e7ffa2f 01APR2026 11:28:59

That’s a complete, renderable table. To produce a file:

spec |> fr_render("Table_14_1_1.rtf")
spec |> fr_render("Table_14_1_1.pdf")
spec |> fr_render("Table_14_1_1.html")

Same spec, any format. The file extension controls the output.

Production-ready table

Real pharma tables need column labels, N-counts, footnotes, and page chrome. Start by setting shared formatting once with fr_theme() — every table in the session inherits it:

# ── Set once per study program (or use _arframe.yml) ──
fr_theme(
  font_size   = 9,
  font_family = "Times New Roman",
  orientation = "landscape",
  hlines      = "header",
  header      = list(bold = TRUE, align = "center"),
  n_format    = "{label}\n(N={n})",
  footnote_separator = FALSE,
  pagehead    = list(left = "TFRM-2024-001", right = "CONFIDENTIAL"),
  pagefoot    = list(left = "{program}",
                     right = "Page {thepage} of {total_pages}")
)

n_itt <- c(placebo = 45, zom_50mg = 45, zom_100mg = 45, total = 135)

Now each table only specifies what is unique to it:

spec <- tbl_demog |>
  fr_table() |>
  fr_titles(
    "Table 14.1.1",
    "Demographics and Baseline Characteristics",
    "Intent-to-Treat Population"
  ) |>
  fr_cols(
    .width = "fit",
    characteristic = fr_col("", width = 2.5),
    placebo        = fr_col("Placebo", align = "decimal"),
    zom_50mg       = fr_col("Zomerane 50mg", align = "decimal"),
    zom_100mg      = fr_col("Zomerane 100mg", align = "decimal"),
    total          = fr_col("Total", align = "decimal"),
    group          = fr_col(visible = FALSE),
    .n = n_itt
  ) |>
  fr_rows(group_by = "group", blank_after = "group") |>
  fr_footnotes("Percentages based on number of subjects per treatment group.")
fr_validate(spec)
TFRM-2024-001 CONFIDENTIAL
Table 14.1.1
Demographics and Baseline Characteristics
Intent-to-Treat Population
Placebo
(N=45)		 Zomerane 50mg
(N=45)		 Zomerane 100mg
(N=45)		 Total
(N=135)
Subjects, n 45 45 45 135
Age (years)
Mean (SD) 75.0 (6.75) 73.1 (8.43) 75.3 (7.09) 74.4 (7.46)
Median 74.0 74.0 73.0 74.0
Min, Max 65.0, 88.0 55.0, 88.0 55.0, 88.0 55.0, 88.0
Age Group, n (%)
<65 0 7 (15.6) 1 ( 2.2) 8 ( 5.9)
65-80 36 (80.0) 29 (64.4) 31 (68.9) 96 (71.1)
>80 9 (20.0) 9 (20.0) 13 (28.9) 31 (23.0)
Sex, n (%)
Female 27 (60.0) 28 (62.2) 20 (44.4) 75 (55.6)
Male 18 (40.0) 17 (37.8) 25 (55.6) 60 (44.4)
Race, n (%)
White 38 (84.4) 32 (71.1) 35 (77.8) 105 (77.8)
Black or African American 1 ( 2.2) 5 (11.1) 5 (11.1) 11 ( 8.1)
Asian 6 (13.3) 6 (13.3) 5 (11.1) 17 (12.6)
American Indian or Alaska Native 0 2 ( 4.4) 0 2 ( 1.5)
BMI (kg/m2)
Mean (SD) 27.1 (4.76) 26.5 (4.60) 24.9 (5.81) 26.1 (5.13)
Median 27.8 25.9 24.6 25.8
Min, Max 18.7, 42.3 17.3, 36.5 14.2, 44.5 14.2, 44.5
MMSE Score at Baseline
Mean (SD) 19.9 (3.51) 19.8 (3.36) 19.5 (3.55) 19.7 (3.45)
Median 20.0 20.0 19.0 20.0
Min, Max 13.0, 26.0 13.0, 26.0 13.0, 26.0 13.0, 26.0
Study Completion, n (%)
Completed 44 (97.8) 41 (91.1) 37 (82.2) 122 (90.4)
Discontinued 1 ( 2.2) 4 ( 8.9) 8 (17.8) 13 ( 9.6)
/tmp/RtmpKCCmfM/callr-scr-6801c2e7ffa2f Page 1 of 1

Notice what is not in the table program: header styling, hlines, page headers/footers, N-format, footnote separator — the theme handles all of it. This is how production study programs work. See Automation & Batch for the full pattern.

Table anatomy

Every pharma table has the same structural regions. Here’s how they map to arframe verbs:

+------------------------------------------------------------------------+
| Protocol TFRM-2024-001                                    CONFIDENTIAL |<- fr_pagehead()
+------------------------------------------------------------------------+
|                                                                        |
|                           Table 14.1.1                                 |<- fr_titles()
|               Demographics and Baseline Characteristics                |
|                                                                        |
| ---------------------------------------------------------------------- |
|                  Placebo    Zomerane 50mg   Zomerane 100mg    Total    |<- fr_cols() +
|                   (N=45)      (N=45)          (N=45)        (N=135)    |   fr_cols(.n=)
| ====================================================================== |<- fr_hlines()
| Age (years)                                                            |
|   Mean (SD)    68.2 (7.1)   67.8 (6.9)     68.0 (7.3)    68.0 (7.1)    |<- data rows
|                                                                        |
| Sex, n (%)                                                             |<- fr_rows(blank_after=)
|   Male         26 (57.8)    24 (53.3)      25 (55.6)     75 (55.6)     |
| ---------------------------------------------------------------------- |
| Percentages based on number of subjects per treatment group.           |<- fr_footnotes()
+------------------------------------------------------------------------+
| t_demog.R                                                 Page 1 of 1  |<- fr_pagefoot()
+------------------------------------------------------------------------+

10 verbs, 10 regions. Learn the verbs, build any table.

The pipeline

Every verb takes a spec, returns a spec. Verb order doesn’t matter — arframe resolves everything (widths, N-count labels, page breaks) at render time.

data |>
  fr_table()    |>   # create spec
  fr_titles()   |>   # add titles
  fr_cols()     |>   # configure columns, N-counts
  fr_header()   |>   # style the header row
  fr_rows()     |>   # row grouping, pagination
  fr_hlines()   |>   # horizontal rules
  fr_styles()   |>   # cell-level formatting
  fr_render("out.rtf")  # produce output

What’s next

I want to… Read
Configure columns, widths, decimal alignment Columns & Headers
Add N-counts to column headers Columns & Headers
Write titles, footnotes, superscripts Titles & Footnotes
Group rows, paginate, indent, group_label Rows & Page Layout
Add borders, spanning headers, cell colors Rules, Spans & Styles
Copy a complete table recipe Table Cookbook
Create listings or embed figures Listings & Figures
Set up study-wide defaults, batch render Automation & Batch
Understand the internals Architecture